Domino Data Lab

JULY 28, 2021

Data science is an exciting, interdisciplinary field that is revolutionizing the way companies approach every facet of their business. Data Science — A Venn Diagram of Skills. Data science encapsulates both old and new, traditional and cutting-edge. 3 Components of Data Science Skills.

Data Science 110

Data Science Statistics Recreation/Entertainment Predictive Analytics 110

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Rocket-Powered Data Science

JULY 13, 2023

Beyond the early days of data collection, where data was acquired primarily to measure what had happened (descriptive) or why something is happening (diagnostic), data collection now drives predictive models (forecasting the future) and prescriptive models (optimizing for “a better future”).

Analytics 167

Analytics Machine Learning Data Science Deep Learning 167

CIO Business Intelligence

JUNE 14, 2023

Certification of Professional Achievement in Data Sciences The Certification of Professional Achievement in Data Sciences is a nondegree program intended to develop facility with foundational data science skills. How to prepare: No prior computer science or programming knowledge is necessary.

Big Data 124

Big Data Data Analytics Analytics Predictive Modeling 124

DataRobot Blog

JULY 28, 2022

Of course, finding a compromise is necessary to a certain degree, but rather than simply compromising, finding the optimal solution within that trade-off is the key to creating maximum business value. Ultimately, the evaluation is based on whether or not the model delivers success to the customers’ business.

Data Science 72

Data Science Machine Learning Statistics Modeling 72

Rocket-Powered Data Science

OCTOBER 6, 2023

Decades (at least) of business analytics writings have focused on the power, perspicacity, value, and validity in deploying predictive and prescriptive analytics for business forecasting and optimization, respectively. Another way of saying this is: given some desired optimal outcome Y, what conditions X should we put in place.

Business Analytics 157

Business Analytics Prescriptive Analytics Analytics Diagnostic Analytics 157

Domino Data Lab

JULY 9, 2019

Chris Wiggins , Chief Data Scientist at The New York Times, presented “Data Science at the New York Times” at Rev. Wiggins also indicated that data science, data engineering, and data analysis are different groups at The New York Times. Session Summary. Transcript. Feel free to email me.

Data Science 112

Data Science Machine Learning Advertising Modeling 112

CIO Business Intelligence

MAY 21, 2024

With this model, patients get results almost 80% faster than before. Next, Northwestern and Dell will develop an enhanced multimodal LLM for CAT scans and MRIs and a predictive model for the entire electronic medical record.

IT 124

IT Cost-Benefit Experimentation Forecasting 124

Smarten

MARCH 5, 2024

The Citizen Data Scientist phenomenon is in full swing and, while the approach has its detractors, the proof is in success, and many organizations are actively succeeding using the Citizen Data Scientist approach. There are many factors and components inherent in the success of a Citizen Data Scientist.

Predictive Modeling 62

Predictive Modeling Consulting Machine Learning Visualization 62

The Unofficial Google Data Science Blog

DECEMBER 4, 2019

by THOMAS OLAVSON Thomas leads a team at Google called "Operations Data Science" that helps Google scale its infrastructure capacity optimally. At least one of the forecast methods will have a quantitative prediction interval generated by the data scientist, so that other forecasts can be considered in the context of this range.

Forecasting 113

Forecasting Data Science Statistics Uncertainty 113

Smarten

FEBRUARY 7, 2020

Assisted Predictive Modeling: The Word ‘Assisted’ is the Key! Assisted predictive modeling! It is true that without the skills and knowledge of a data scientist or a business analyst, predictive analysis can be a daunting task. The term sounds complex and intimidating, doesn’t it?

Predictive Analytics 67

Predictive Analytics Predictive Modeling Analytics Software 67

Smart Data Collective

SEPTEMBER 16, 2020

Predictive analytics, sometimes referred to as big data analytics, relies on aspects of data mining as well as algorithms to develop predictive models. These predictive models can be used by enterprise marketers to more effectively develop predictions of future user behaviors based on the sourced historical data.

Predictive Analytics 121

Predictive Analytics Analytics Predictive Modeling Data mining 121

Smarten

FEBRUARY 28, 2019

If Data Science was once the sole domain of analysts and data scientists, Augmented Data Science represents the democratized view of this domain. Augmented data science automates and simplifies analysis with machine learning so implementation, training and adoption of these tools is rapid and successful.

Data Science 40

Data Science IT Machine Learning Predictive Modeling 40

Smarten

FEBRUARY 7, 2019

The Gartner report entitled, ‘Augmented Analytics Is the Future of Data and Analytics, published on October 31, 2018, includes the following strategic assumptions: By 2025, a scarcity of data scientists will no longer hinder the adoption of data science and machine learning in organizations.

Optimization 40

Optimization Analytics Predictive Modeling Data-driven 40

DataRobot

NOVEMBER 1, 2021

Practitioners in the AI space are focused on the speed and accuracy of model predictions. But the end game for the applicability of models is not in the predictions, but the decisions they enable, and predictive models alone don’t ensure better decisions.

Machine Learning 98

Machine Learning Manufacturing Predictive Modeling Optimization 98

CIO Business Intelligence

MAY 9, 2024

At a high level, a CAIO will need to understand the business well enough to identify where AI can make an impact, whether through new value streams or optimization, Daly says. They also need to understand the vitality of quality data for AI success, as well as governance frameworks to ensure responsible and ethical use of AI.

Risk Management 134

Risk Management Risk Cost-Benefit Technology 134

Smarten

APRIL 25, 2024

Artificial Intelligence (AI) and Machine Learning (ML) elements support Citizen Data Scientists and help users prepare data, achieve automated data insights and create, share and use predictive models.

Data Quality 62

Data Quality Analytics Machine Learning Visualization 62

Smarten

MARCH 13, 2024

For a number of years, Gartner and other technology research and analysis firms have predicted and monitored the growth of this phenomenon. In fact, Gartner predicted that, ‘…40% of data science tasks will be automated, resulting in increased productivity and broader usage by citizen data scientists.’

Analytics 52

Analytics Predictive Modeling Strategy Enterprise 52

DataRobot

JANUARY 20, 2022

A financial squeeze on healthcare, post-pandemic, is widely regarded as inevitable, and as the NHS recovers, it will need to achieve increased efficiency savings through clinical and operational process redesign and optimization. ICSs can reduce the time taken to build population health registries and predictive models by up to 90 percent.

Data-driven 145

Data-driven Experimentation Modeling Predictive Modeling 145

Smarten

JANUARY 24, 2019

Quite simply, it is the means by which your business can optimize resources, encourage collaboration and rapidly and dependably distribute data across the enterprise and use that data to predict, plan and achieve revenue goals. What is Automated Machine Learning?

Machine Learning 40

Machine Learning Predictive Modeling Predictive Analytics Forecasting 40

IBM Big Data Hub

DECEMBER 20, 2023

ML is a computer science, data science and artificial intelligence (AI) subset that enables systems to learn and improve from data without additional programming interventions. Here, we’ll discuss the five major types and their applications. What is machine learning?

Machine Learning 76

Machine Learning Modeling Deep Learning Predictive Modeling 76

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. Nominations for the 2021 Cloudera Data Impact Awards are open from now until July 23.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

datapine

NOVEMBER 27, 2019

Hotels try to predict the number of guests they can expect on any given night in order to adjust prices to maximize occupancy and increase revenue. There are plenty of big data examples used in real life, shaping our world, be it in the buying experience or managing customers’ data. 1 for data analytics trends in 2020.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Rocket-Powered Data Science

FEBRUARY 12, 2021

This is accomplished by adding more data-driven, machine learning, and AI (artificial intelligence) components to the process discovery, process mining, and process learning stages. IA incorporates feedback, learning, improvement, and optimization in the automation loop. The average ROI from RPA/IA deployments is 250%.

ROI 234

ROI Digital Transformation Reporting Machine Learning 234

DataRobot

JANUARY 13, 2022

But they often don’t have enough data scientists with the full range of domain expertise to realize its full value. Data scientists typically come equipped with skills in three key areas: mathematics and statistics, data science methods, and domain expertise.

ROI 52

ROI Machine Learning Experimentation Data Science 52

Smarten

DECEMBER 17, 2018

My business users don’t have the skill, the patience or the time to become data scientists. But, they don’t have to be data scientists to use augmented analytics. With these tools, users can explore patterns in data and receive suggestions to help them gain insight on their own without dependence on IT or data scientists.

Predictive Analytics 40

Predictive Analytics Predictive Modeling Analytics Statistics 40

DataRobot Blog

JUNE 23, 2022

Most successful ML and AI projects are replacing an existing prediction with a more accurate and/or faster one. Human intuition is relied on, or an older, hand-build BI/predictive model exists, or perhaps a set of heuristics were documented that more or less predict something. Case Study.

Predictive Modeling 59

Predictive Modeling Modeling Data Science Measurement 59

datapine

JANUARY 31, 2022

Although the oil company has been producing massive amounts of data for a long time, with the rise of new cloud-based technologies and data becoming more and more relevant in business contexts, they needed a way to manage their information at an enterprise level and keep up with the new skills in the data industry.

Business Intelligence 214

Business Intelligence Analytics Cost-Benefit ROI 214

BI-Survey

JANUARY 29, 2023

For many organizations, modern technology around machine learning (ML) and the cloud, as well as its growing ease of use, offer a great opportunity for optimization. The fact that companies do not shy away from the effort involved shows the high expectations of the potential for accelerating and optimizing planning and forecasting.

Forecasting 52

Forecasting Predictive Modeling Measurement Finance 52

Birst BI

AUGUST 23, 2018

What if some of these data science tasks could be automated using AI, increasing data science productivity to tackle more AI use cases? Automating data science tasks leaves room to build more AI applications with the same amount of data science resources. Source: Gartner (April 2018).

Machine Learning 73

Machine Learning Data Science Testing Metrics 73

Smarten

AUGUST 21, 2019

Smart Data Visualization – Smart Data Visualization gives users a helping hand with suggestions and recommendations for the best possible visualization of underlying data to generate meaningful insights from data. Original Post: Smarten Augmented Analytics: Sophistication and Simplicity.

Analytics 51

Analytics Predictive Modeling Visualization Statistics 51

Business Over Broadway

SEPTEMBER 27, 2018

In our world of Big Data, marketers no longer need to simply rely on their gut instincts to make marketing decisions. Through the application of data science principles, marketing professionals now have a way of making evidence-based decisions to improve their marketing activities. The more data they ingest, the better they get.

Machine Learning 76

Machine Learning Data Integration Marketing Predictive Modeling 76

O'Reilly on Data

SEPTEMBER 19, 2023

While data scientists were no longer handling Hadoop-sized workloads, they were trying to build predictive models on a different kind of “large” dataset: so-called “unstructured data.” Both situations benefit from a technique that optimizes the search through a large and daunting solution space.

Machine Learning 243

Machine Learning Testing Modeling Cost-Benefit 243

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. There are many types of data pipelines, and all of them include extract, transform, load (ETL) to some extent.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

DataRobot Blog

JANUARY 10, 2023

ML model builders spend a ton of time running multiple experiments in a data science notebook environment before moving the well-tested and robust models from those experiments to a secure, production-grade environment for general consumption. Deep Dive into DataRobot Notebooks. Auto-scale compute.

Experimentation 52

Experimentation Machine Learning Data Science Modeling 52

CIO Business Intelligence

MAY 10, 2022

A customer data platform (CDP) is a prepackaged, unified customer database that pulls data from multiple sources to create customer profiles of structured data available to other marketing systems. It requires SQL for optimal use, so is best suited for data engineers and analysts. Treasure Data CDP.

Advertising 104

Advertising Interactive Marketing Data Integration 104

Cloudera

NOVEMBER 18, 2020

To ensure maximum momentum and flawless service the Experian BIS Data Enrichment team decided to use the power of big data by utilizing Cloudera’s Data Science Workbench. To optimize investments, effectively bundle product offerings, and deliver contextual campaigns, Globe Telecom created a new analytical environment.

Internet Publishing and Broadcasting 121

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 121